diff options
Diffstat (limited to 'lib/keysightdlog.py')
-rwxr-xr-x | lib/keysightdlog.py | 85 |
1 files changed, 85 insertions, 0 deletions
diff --git a/lib/keysightdlog.py b/lib/keysightdlog.py new file mode 100755 index 0000000..3864d6e --- /dev/null +++ b/lib/keysightdlog.py @@ -0,0 +1,85 @@ +#!/usr/bin/env python3 + +import lzma +import numpy as np +import os +import struct +import sys +import xml.etree.ElementTree as ET + +filename = sys.argv[1] + +with open(filename, 'rb') as logfile: + lines = [] + line = '' + + if '.xz' in filename: + f = lzma.open(logfile) + else: + f = logfile + + while line != '</dlog>\n': + line = f.readline().decode() + lines.append(line) + xml_header = ''.join(lines) + raw_header = f.read(8) + data_offset = f.tell() + raw_data = f.read() + + xml_header = xml_header.replace('1ua>', 'X1ua>') + xml_header = xml_header.replace('2ua>', 'X2ua>') + dlog = ET.fromstring(xml_header) + channels = [] + for channel in dlog.findall('channel'): + channel_id = int(channel.get('id')) + sense_curr = channel.find('sense_curr').text + sense_volt = channel.find('sense_volt').text + model = channel.find('ident').find('model').text + if sense_volt == '1': + channels.append((channel_id, model, 'V')) + if sense_curr == '1': + channels.append((channel_id, model, 'A')) + + num_channels = len(channels) + duration = int(dlog.find('frame').find('time').text) + interval = float(dlog.find('frame').find('tint').text) + real_duration = interval * int(len(raw_data) / (4 * num_channels)) + + data = np.ndarray(shape=(num_channels, int(len(raw_data) / (4 * num_channels))), dtype=np.float32) + + iterator = struct.iter_unpack('>f', raw_data) + channel_offset = 0 + measurement_offset = 0 + for value in iterator: + data[channel_offset, measurement_offset] = value[0] + if channel_offset + 1 == num_channels: + channel_offset = 0 + measurement_offset += 1 + else: + channel_offset += 1 + +if int(real_duration) != duration: + print('Measurement duration: {:f} of {:d} seconds at {:f} µs per sample'.format( + real_duration, duration, interval * 1000000)) +else: + print('Measurement duration: {:d} seconds at {:f} µs per sample'.format( + duration, interval * 1000000)) + +for i, channel in enumerate(channels): + channel_id, channel_model, channel_type = channel + print('channel {:d} ({:s}): min {:f}, max {:f}, mean {:f} {:s}'.format( + channel_id, channel_model, np.min(data[i]), np.max(data[i]), np.mean(data[i]), + channel_type)) + + if i > 0 and channel_type == 'A' and channels[i-1][2] == 'V' and channel_id == channels[i-1][0]: + power = data[i-1] * data[i] + print('channel {:d} ({:s}): min {:f}, max {:f}, mean {:f} W'.format( + channel_id, channel_model, np.min(power), np.max(power), np.mean(power))) + +#print(xml_header) +#print(raw_header) +#print(channels) +#print(data) +#print(np.mean(data[0])) +#print(np.mean(data[1])) +#print(np.mean(data[0] * data[1])) |